Reinforcement Learning Engineer – Cybersecurity

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Logo of Bugcrowd

Bugcrowd

201 - 500 employees

Founded 2012

🔒 Cybersecurity

☁️ SaaS

🏢 Enterprise

💰 $30M Series D on 2020-04

Cybersecurity • SaaS • Enterprise

Bugcrowd is a leading platform that provides continuous security testing solutions, enabling organizations to stay ahead of cyberthreats. By leveraging a global community of trusted security researchers, Bugcrowd offers services such as penetration testing as a service, vulnerability disclosure, bug bounty programs, and attack surface management. The company assists industries such as financial services, healthcare, and technology in identifying and prioritizing vulnerabilities, ensuring proactive protection against potential cyber attacks. Driven by data and AI, Bugcrowd's comprehensive approach integrates seamlessly with existing systems to streamline the remediation of security issues, enhancing the overall security posture of its clients.

📋 Description

• Advance the frontier of AI Reinforcement Learning development and delivery • Build the infrastructure and tooling that transforms real-world vulnerability research into large-scale reinforcement learning environments • Create training environments that teach AI systems how to hack and defend software • Work at the intersection of AI, security research, and systems engineering

🎯 Requirements

• Strong systems engineer • Understanding of RL training workflows used by modern LLM systems • Experience with DevOps pipelines (e.g., github actions), reproducible builds (docker, buildkit, nix) • Proficiency in Python and C. Other languages (especially Rust) are a plus • Understanding of software vulnerabilities, fuzzing, or program analysis • Experience with build systems and large open-source codebases • Comfort working with Linux systems and low-level debugging • Experience working with benchmark environments (CTFs, SWE-bench, security challenges, etc.) is a plus

🏖️ Benefits

• Discretionary bonus program • Commission plan

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